aculty m 62 educause r e v i e

8/14/2019 Aculty M 62 EducausE r e v i e

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Ed u cau s E r e v i e w sep tember /O tober 2007 © 2 0 0 7 J o e l L . H a r t m a n , C h a r l e s D z i u b a n , a n d J a m e s B r o p h y - E l l i s o n

By Joel L. Hartman, charles dziuban, an James Brophy-Ellison

Joel L. Hartman is Vice Provost for Information Technologies and Resources, University of CentralFlorida. Charles Dziuban is Director of the Research Initiative for Teaching Effectiveness, Universityof Central Florida. James Brophy-Ellison is Senior Faculty Fellow at the Research Initiative for Teach-ing Effectiveness, University of Central Florida.

Much has been written recently about the Net Gen-eration—the generation (roughly twelve to twenty-five years old) that makes up the majority of stu-dents attending U.S. colleges and universities—butrelatively little attention has been given to the col-lege and university faculty who teach them. Faculty roles and the processes of teaching and learningare undergoing rapid change. Most faculty mem-

bers did not seek careers in the academy because of a strong love oftechnology or a propensity for adapting to rapid change; yet they now find themselves facing not only the inexorable advance of technology into their personal and professional lives but also the presence intheir classrooms of technology-savvy Net Generation students, lead-ing them to feel a bit like the character Valentine Michael Smith inRobert Heinlein’s 1961 novelStranger in a Strange Land.

I l l u s t r a t i o n b y J e ff r e y S m i t h , © 2 0 0 7 sep tember /O tober 2007 Ed u cau



64 EducausE e v e w sep tember /O tober 2007

The three traditional roles of col-lege and university faculty are teaching,research, and service, with the relativeemphasis on each varying by institutionaltype and mission. Each of these roles is un-dergoing substantial change, but teachingand research are being most significantly altered by technology. The growing im-pact of technology on research has beenwell documented in recent publications:the National Research Council’sPrepar-ing for the Revolution: Information Technologyand the Future of the Research University; theNational Science Foundation’sCyberin- frastructure Vision for 21st Century Discovery;and reports from the EDUCAUSE Centerfor Applied Research (ECAR), includingWhat Do Researchers Need? Higher EducationIT from the Researcher’s Perspectiveand IT and the Changing Face of Research in Higher Education. These publications, and many others, chronicle the transformation thatis under way in research tools and meth-ods, in the composition of research teams,and even in the structure of academic dis-ciplines. Nearly every discipline has beenredefined to some extent by technology,and entirely new branches of traditionaldisciplines are emerging. A recentGoogle search for the wordcomputational conjoined with the names of traditionalfields of study revealed more than thirty

newly defined fields, ranging from com-putational astrophysics to computationalzoology. As the title of aNew York Times column by George Johnson suggests, “AllScience Is Computer Science.”1

Although research and publicationare undeniably important componentsof the professional lives of many faculty members—for some, they formthemostimportant component—we are focusinghere on the less-visible changes broughtabout by technology in the teachingand learning space and on how these

changes are fundamentally reshaping theprocesses and tools associated with theinstitutional structures, extending to theroles and responsibilities of campus ITleaders and organizations. For the firsttime in their careers, faculty membersare expected to teach in ways that differfrom how they were taught when they were students. Diana G. Oblinger andMark K. Maruyama have observed thathistorically, at a majority of institutions,

lecturing has been equated with teaching:approximately 80 percent of instructionhas been delivered in this mode. Yet eventhough lecture-based classroom teachinghas long been held as the “gold standard”against which newer, technology-enhanced methods are often compared,

A. H. Johnstone and W. Y. Su have notedhow inefficient lecturing can be as ameans of conveying information. Thetypical lecture contains approximately 5,000 words, of which a student may cap-ture about 500—a mere 10 percent.2

Over the past two decades, broad andrapid advancements in new theories oflearning, new student-centered pedago-gies, and new online- and classroom-based interactive technologies havebegun to enable the pedagogical changescalled for by Oblinger and Maruyama.

Donald P. Buckley referred to this shift asa transformation from ateaching-centeredtoa learning-centeredparadigm,3 as elaboratedby Robert B. Barr and John Tagg (seeTable 1).

In 1995 the Campus Computing Sur- vey, an annual study of IT activities andpriorities in higher education conductedby Kenneth C. Green, documented amajor shift in the use of technology tosupport instruction. Before 1995, survey

responses noted general growth in thavailability and use of various instructional technologies on U.S. campuseHowever, in 1995, Green reported ththe survey data indicated that “the use oinformation technology in instructionwas “finally moving past the early adop

ers and breaking into the ranks of mainstream faculty” at all types of institution4 Instructional integration of IT remainethe number-one issue as reported bythe Campus Computing Survey through2003, after which network and datsecurity bumped it to the number-twoposition.

The diffusion of technology into thteaching and learning space is producina number of subtle—and not-so-subtlechanges to which faculty members muadapt:

n Most faculty members are experts itheir respective disciplines, and ateachers, they expect to be regarded asuch. Confronting new and unfamiliatechnologies can quickly turn theminto novices, and with technicallysavvy Net Generation students itheir classes, they may find that thestudents know much more abouspecific technologies than they do

TABLE 1. Differences between Teaching-Centeredand Learning-Centered Approaches

Teaching-cenTered Learning-cenTered

Deliver instruction Produce learningTransfer of knowledge from teacher tostudent

Discovery and construction of knowledge

Active faculty Active studentsOne teaching style Multiple learning stylesCurriculum development Learning technologies developmentQuantity and quality of resources Quantity and quality of outcomesQuality of faculty Quality of studentsTime held constant; learning varies Learning held constant; time variesLearning is linear and cumulative Learning is a nesting and interacting of

frameworksPromote recall Promote understandingFaculty are lecturers Faculty are designers of learning

environments

Learning is competitive and individualistic Learning is cooperative and collaborativeSource:Robert B. Barr and John Tagg, “From Teaching to Learning: A New Paradigm for UndergraEducation,”Change, vol. 27, no. 6 (November/December 1995): 12–25.




creating a balance-of-power shift inthe faculty-student relationship. WhenFrancis Bacon stated that “knowledgeis power,” he could not have imaginedthe role that technology would one day play in the dissemination and acquisi-tion of knowledge. Today, studentsare increasingly prepared to abandonlibraries and class attendance in favorof the Internet as the most expedientpath to knowledge.

n Net Generation students use a range oftechnologies and information sourcesthat are often unfamiliar to their teach-ers, who may be from older Gen-X,Boomer, or Mature generations. Whenfaculty communicate through tech-nology, they are likely to use e-mail.By contrast, their Net Generationstudents communicate with peersthrough instant messages (IMs), usinge-mail for communicating with “oldpeople” or institutions.5

n Although the quality of students’ writ-ing has long been a concern, faculty are recently reporting a sharp decline,

which some attribute to the increasingpopularity of IM and also cell phonetext-messaging.

n Faculty members see their studentsas individual learners and regardstudents who complete assignmentswith others as cheaters. However, NetGeneration students exhibit strong so-cial behavior patterns and value socialnetworking, working in groups, andexperiential learning. Net Generationstudents’ social groups extend beyondpeople they know directly and include

others whom they encounter on socialnetworking sites as friend-of-a-friendcontacts. Students prefer and expectto work in groups.

n Course management systems, cellphones, iPods, and other populartechnologies have been used by stu-dents to commit acts of intellectualdishonesty, requiring faculty membersto be vigilant, to establish rules forwhen and how technology can be used

in class, and to modify the ways they assess student learning. In regard to as-sessment, the Net Generation’s ability to create information products affordsnew, more authentic and contextualmeans of assessing student learning.

n The increasingly vast array of onlineinformation, social networking Websites, digital media, and other onlineresources has greatly increased oppor-tunities for informal learning, leadingto an environment in which learningopportunities outside the classroommay far exceed those within.

n Net Generation students grew upexposed to television and interactivemedia and are consequently more visually literate than previous genera-tions. At the same time, these studentsare reading less than did previousgenerations. This shift from textualto visual literacy is leading somestudents to avoid reading, includingassignments and lengthy questions onexams. Some faculty members are ad-justing to the shift in students’ literacy

by using more visual and interactivemedia in their classes.n The way that faculty members use

their time is also shifting. Traditionally,faculty members would be in class, intheir offices, in their labs or elsewheredoing research, or off campus and in-accessible. Students now expect theirinstructors to be accessible via e-mailat nearly any hour and to respond toe-mails within minutes. Many faculty members report that they are devot-ing more time to their work and that

their work time is spread over a largerportion of the day because they cancommunicate with students via e-mailor through a course managementsystem.

n Students assume that everything isonline and that everything online isfree. Many faculty members, however,consider their course materials andnotes to be their intellectual property.Instructors are appalled, therefore,

when they find that an enterprisingstudent has posted lecture notes to social networking site or, worse, to Web site that is selling lecture noteand exam questions contributed bystudents.

n Faculty members think of technology as technology. Students think otechnology as environment. Facultuse technology as tools for presentincontent. Students use technology atools for exploring, communicatingand socializing. When asked aboutheir preferences for the use of technology in their classes, students consistently report that they desire “moderate” incorporation into the learninenvironment.6 This is not becausethey dislike technology but, ratherbecause they see it as a tool for actilearning instead of as a tool to facilitathe instructor’s presentation of information. Marc Prensky refers to todaystudents as “digital natives” in recogntion of the fact that they have neveknown a world in which computers

the Internet, the Web, and digitamedia did not exist. Older generationincluding most faculty and administrators, are “digital immigrants” whhave come to use technology later itheir lives and whose “digital accentare discernible to their students.

n A plethora of social networking anresource-sharing sites has appearedover the past few years, includinFacebook, Myspace, Flickr, YouTubLiveJournal, Twitter, and Second LifStudents have increasingly turned to

these sites as the nexus of their sociand even academic universe. Facultmembers are beginning to followusing these sites as a means of gettinto know their students, as a rapid anreliable way to reach students, and asmethod for sharing faculty-producedand student-produced content.

n Although faculty members are assocated with departments, disciplinesand various campus organizations, i

Students assume that everything is online and that everything onMany faculty members, however, consider their course materialsbe their intellectual property.




their roles as teachers they generally act as individuals. The need to under-stand and apply technology bringsabout a greater dependency on a widerange of others, including help-desk staff, trainers, faculty developers, in-structional designers, and even theirstudents.

n Technology has the potential to affectthe three “Rs”: reward, recognition,and risk. Faculty who devote largeamounts of time to learning about andapplying technology in their coursesmay not be rewarded or recognized forthat work and, worse, may find that theadditional time spent with technology takes time away from their researchand publication activities, whichmight place them at risk regardingtenure or promotion.

Teaching ExcellenceEmerging technologies are modifyingthe relationships between instructorsand students, making the determination

of quality teaching in higher educa-tion more complex and difficult. Henry Jenkins calls this processconvergence, inwhich faculty deal with course contentacross multiple media platforms, pro-ducing compound learning environ-ments—some of which are created andmediated by students.7 In a sense, theprofessoriate is becoming unbundledjust as music selection has become an àla carte activity rather than a centralizedservice; no longer are instructors the solesource of information. More than ever,

students are consumers as they learncollaterally across dispersed contentemanating from games and media thatforce complex decision-making andwith technologies that permit them torewind and replay.8 This environmentmoves higher education away from atransmission-of-information model andtoward a culture in which teaching excel-lence becomes a multifaceted construct.

The popularity of RateMyProfessors

.com demonstrates that students’ assess-ment of instruction is moving from thehistorically staid rating system, in whichrespondents rarely experience any re-sults from their responses on the teachingand learning process, to a social network-ing phenomenon, in which evaluationhappens within a worldwide community.Given the current interest in how NetGeneration learning styles differ fromthose of earlier generations, we might ask: What components underpin students’perception of excellent teaching by faculty in this emerging environment ofenhanced instructional technology?

At the University of Central Florida(UCF), an unanticipated side effect ofteaching in a technology-enhancedenvironment arose from faculty mem-bers’ concerns that their evaluations by

students would suffer simply because theassessment-of-instruction instrument,which was originally developed to assessface-to-face classroom instruction, was

inconsistent with various technology-mediated class-delivery modalities now incommon use. To address these concerns,UCF undertook a series of data-miningstudies encompassing more than 700,000end-of-term instruction ratings by stu-dents, leading to the discovery of a set ofdecision rules for the conditions underwhich students assign an overall rating of“excellent” to a course and its instructor.9 These studies produced a primary deci-sion rule that leads to a high probability that an instructor will receive an overall

rating of “excellent”: if students rate aninstructor as “superior” on the two (out ofsixteen) items that assess his or her ability to facilitate learning and to communicateideas and information, then the chancesare very good (.92) that he or she will begiven an overall “excellent” rating. Thisrule holds true for face-to-face, blended,fully online, or any other course-delivery modality and is not affected by collegeaffiliation or course level. Other course

elements—such as good organizatioclear expectations, effective use of timauthentic assessment techniques, and demonstrated interest in students’ learning—have some influence, but facilitatiand communication become the dominant influences on students’ ratings.

The Net Generation values recogntion, respect, responsiveness, and rewarfrom their instructors, whether they arin an online or face-to-face course. Whestudents experience those elementsthey see excellence. A content review the narratives in RateMyProfessors.coreveals a consistently large number ocomments that reflect those dimensionand instructors’ ability to engage thestudents. In that respect, the Net Generation is no different from Baby Boomers Generation X. What is unique is the hig

level of expectations that Net Generatiostudents hold for professors to establisinteractive learning environments andto have a working familiarity with th

growing number of Web-based instructional resources. Teaching excellence becoming what Susan L. Star has termea boundary object—a concept that is shareby many and used to bring multiplconstituencies together but that is understood differently by each constituency.10 Consider, for example, how CIOs, othcampus administrators, tenure-trackfaculty, instructors, students, and parentof students might describe the prototyp“excellent” instructor. There would bcommonality, but there would be grea

divergence as well.Jenkins claims that new media winot replace old media; instead, old annew media will interact and converge.11 A good example of that phenomenon mabe seen in the increasing attention beingiven to blended learning, in which thprior modality (face-to-face) is convering with the new modality (online). Jekins argues that entrenched institutionwill develop new models for teachin

Emerging technologies are modifying the relationships betweenstudents, making the determination of quality teaching in highercomplex and dif cult.




from grassroots communities, thereby reinventing themselves from mediaconvergence and collective intelligence. As a caveat, we add that determiningteaching excellence involves far morethan students’ ratings of instructors andthat there are many who question the validity of that process. However, it seemsclear that student communities play animportant role in framing instructionalmodels.

Faculty DevelopmentThe above changes do not affect allfaculty members equally. First, not allfaculty members are equally engaged inteaching; second, those who are deeply engaged may differ in their willingnessto explore or adopt technology in theirteaching. Everett M. Rogers studied thediffusion of innovation throughoutorganizations. Rogers’s “diffusion of in-novations” model, depicted in Figure 1,suggests that members of an organization(e.g., college or university faculty) are nothomogeneous but rather can be classifiedas sub-populations based on the order inwhich they are likely to become engagedwith an innovation. Rogers labels thesesub-populations as innovators (I), early adopters (EA), early majority (EM), latemajority (LM), and laggards (L). Innova-

tors are the few pioneers who are first toexperiment with a new concept and put

it to use. Often having advanced technicalskills, innovators bring attention to the in-novation within the organization, where

it is subsequently observed and thenattempted by the early adopters. Early adopters are the first to begin moving theinnovation into the mainstream, and thegreater the visibility and credibility of thisgroup, the more likely the innovation is tobe adopted by the early and late majori-ties. The final category, laggards, is namedin recognition of its members’ relativeunwillingness to give up their traditionalbeliefs and practices.

If we apply Rogers’s model to faculty members’ adoption of technology inteaching, several points become appar-ent. First, the motivations, incentives, andsupport required for each populationof adopters are different. At each stage,the adopters become more pragmatic,less likely to adopt an innovation forits own sake, and more entrenched intraditional beliefs and practices. It willtherefore take higher levels of energy andresources to support an innovation suchas technology-facilitated teaching andlearning as it moves through an institu-tion. Second, after an innovation passes

from the early adopters to the early andlate majorities, the size of the population

that must be supported increases dramat-ically. Third, the later stages of diffusionwill involve large populations at various

levels of adoption, bringing the new chal-lenge of supporting multiple populationswith differing needs and attitudes.

Tony Bates explains how to apply Rogers’s model to the design of effec-tive faculty-development programs.12 He cautions that although providingdirect support to individual early adopt-ers—what Bates calls the “Lone Ranger”faculty-development model—may seemattractive to IT organizations, the result-

ing initiatives often do not scale becausthey are heavily dependent on one oonly a few individuals. Bates cautions thfaculty enthusiasm and self-reliance manot be sufficient to ensure the diffusioof these efforts institution-wide. Batessecond faculty-development model ithe “boutique approach.” Boutique solutions provide one-on-one support tofaculty members as they come forwarand request assistance. This model satisfying to both faculty and profesional staff—until the number of faculmembers requiring support begins toincrease. Although boutique project

may themselves be scalable, the support structure is not, eventually leadin

to the “support crisis” present on mancampuses. In Bates’s third model—thsystemic approach—campus suppo

resources, including instructional designers, programmers, and digital medispecialists, are brought together under common strategy, scaffolded by scalabsystems and by processes for dealing wirapidly increasing support needs. Returon investment is improved by designinsystems that scale for enterprise-widdelivery as opposed to developing whChris Dede calls “islands of innovation13

Because teaching with technolog

The later stages of diffusion will involve large populations at vaadoption, bringing the new challenge of supporting multiple popdiffering needs and attitudes.

FigurE 1. “Diffusion of Innovations” Model

Source: Everett M. Rogers,Diffusion of Innovations, 4th ed. (New York: Free Press, 1995), p. 262.




is in a constant state of beta or, as JanosSetenyi says, a state of “uncertain media-tion,”14 faculty development needs to beorganic and continuous. Resources thathave potential for improving teachingappear on a daily basis, but integratingthose teaching assets into an instructionalplan and then implementing them isan arduous task. Real-time professionaldevelopment puts increasing pressure onfaculty-development centers to be muchless place-centric. The centers may evolveinto clearinghouses where faculty mem-bers can share with each other on a peer-to-peer basis, possibly involving studentsin the development process. The obviousenabling constructs for such an arrange-ment will be information technology andinstructional technology: the “two ITs.” IfThomas L. Friedman is correct in ascer-taining that the world economy is gravi-tating from countries and multinationalcorporations to individuals in the worldmarketplace,15then the same must be truefor higher education. Certainly knowl-edge disperses itself in a much more hori-

zontal structure than ever before. Justas academic libraries are moving away from being the atomistic centers of theircolleges or universities, faculty membersneed to become the critical component ina broader network of peer-to-peer profes-sional development. This represents afundamental cultural shift.

Steve Ehrmann, in the blogTLT-SWG ,suggests another model for faculty devel-opment: “Academic programs could domuch better (in all senses of ‘better’) if they helped their faculty become the best at a)finding and adapting best practices frompeers [at other institutions] who teachsimilar courses, and b) sharing their ownbest practices with the world.”16If this wereto come to pass, the implications for ITunits of colleges and universities wouldbe profound, as they would be also foracademic reward structures for teachingexcellence and faculty development.

In addition, students have a perspec-tive that influences faculty development.Brenna Veale, a student from the Uni- versity of South Carolina, responded to a

presentation by Chuck Dziuban: “As yosaid, someone of the mature generatiomight sit down and read the manual fornew cell phone. My generation will learby interaction with the phone itself othrough a social network, not by passiveisolating oneself and following the narative of the manual. My main questiothen, is this: is the current way of measuing critical thinking outdated?”17

A Moving TargetEverything has changed, is changing, anwill continue to change: students, facultresearch, the processes of teaching anlearning, and of course, technologies. Thimplications of research 2.0, teaching anlearning 2.0, and faculty 2.0 for campusleaders and organizations are both broaand deep. Only within the past few yeahas central support for research, instructional technology, faculty developmenand instructional infrastructure begunto appear as an element of the CIOportfolio. The 2007 EDUCAUSE CurreIssues Survey gives a sense of how th




change is occurring across the spectrumof institutional types and sizes.18 In termsof how IT leaders are spending theirtime, CIOs at large or doctoral-researchinstitutions report that research sup-port is among their top-ten IT-relatedissues, whereas CIOs at small-to-mediuminstitutions and those at master’s, bac-calaureate, and associate’s institutions donot. Conversely, CIOs at master’s, bacca-laureate, and associate’s institutions andthose at small-to-medium institutions aremore likely to report that faculty develop-ment and support, course managementsystems, and electronic classrooms areamong their top-ten IT-related issues.The survey clearly shows, however, thatthe infrastructure to support technology-enhanced instruction—course manage-ment systems, electronic classrooms, and

e-learning—has become an area whereinstitutions of all types and sizes arespending significant human and finan-cial resources.

The above changes will challenge ITleaders in many ways. They must becomefamiliar with new technologies (those thatare supported by the institution as wellas many that are not), understand andserve new populations of faculty at vary-ing levels of sophistication, find the fiscaland human resources to support andsustain these new initiatives, and adapttheir organizations to serve new missions.This will require modifying existingorganizational structures (e.g., addinginstructional designers and digital mediaproducers) or forming new campus part-nerships with instructional technology organizations in order to create a much

broader network for supporting teachinand learning.

As faculty members confront thexpanding impact that technology ihaving on their scholarship, researchteaching, and students—what Peter Vacalls “Permanent White Water”—IT oganizations must assess what role thewill play in shaping, implementing, ansupporting the assimilation of IT into thteaching and learning process. Shoulthe goal be to persuade and assist faculmembers to adopt technology, or shoulit be to enable systemic transformation When technology is “bolted on” to existing process, the usual result is modest improvement in the process analso higher costs.19To obtain both greaterimprovement and reduced costs, higheeducation institutions must redesign the

IT organizations must assess what role they will play in shapingimplementing, and supporting the assimilation of IT into the teaand learning process.




process so as to take maximum advantageof the enabling capabilities of technolo-gies. Such initiatives, as Bates suggests,will ultimately produce the greatestbenefit for the largest number of faculty in a manner that aligns with institutionalgoals, is sustainable, and will lead totransformation at course, program, andinstitutional levels.e

Notes1. George Johnson, “The World: In Silica Fertiliza-

tion; All Science Is Computer Science,”New YorkTimes, March 25, 2001, <http://query.nytimes.com/gst/fullpage.html?sec=technology&res=9E02E6DD123CF936A15750C0A9679C8B63>.

2. Diana G. Oblinger and Mark K. Maruyama,Distributed Learning , CAUSE Professional PaperSeries, #14 (Boulder, Colo.: CAUSE, 1996); A. H.Johnstone and W. Y. Su, “Lectures: A LearningExperience?”Education in Chemistry, vol. 31, no. 3(1994): 75–79.

3. Donald P. Buckley, “In Pursuit of the LearningParadigm,”EDUCAUSE Review, vol. 37, no. 1 (Janu-ary/February 2002): 28–38.

4 Kenneth C. Green,The Campus Computing Project:The 1995 National Survey of Information Technology inHigher Education(Encino, Calif.: Campus Comput-ing Project, 1996).

5. Amanda Lenhart, Mary Madden, and Paul Hitlin,

Teens and Technology(Washington, D.C.: Pew Inter-net & American Life Project, 2005).

6. Gail Salaway, Richard N. Katz, Judith B. Caruso, etal., “The ECAR Study of Undergraduate Studentsand Information Technology,”EDUCAUSE Center for Applied Research (ECAR) Research Study, vol. 7(2006), <http://connect.educause.edu/library/abstract/TheECARStudyofUnderg/41172>.

7. Henry Jenkins,Convergence Culture: Where Old andNew Media Collide(New York: New York University Press, 2006).

8. See Steven Johnson,Everything Bad Is Good for You:How Today’s Popular Culture Is Actually Making UsSmarter , 1st paperback ed. (New York: RiverheadBooks, 2006).

9. Charles D. Dziuban, Morgan C. Wang, and Ida J.Cook, “Dr. Fox Rocks: Student Perceptions of Ex-cellent and Poor College Teaching” (unpublishedmanuscript, University of Central Florida, 2004).

10. Susan L. Star, “The Structure of Ill-StructuredSolutions: Boundary Objects and HeterogeneousDistributed Problem Solving,” in M. Huhns and L.

Gasser, eds.,Distributed Artificial Intelligence(MenloPark, Calif.: Kaufmann, 1989), 2:37–54.

11. Jenkins,Convergence Culture.12. Tony Bates,Managing Technological Change:

gies for College and University Leaders(San Francisco,Calif.: Jossey-Bass, 20 00).

13. Christopher Dede, “Distance Learning–DistributLearning: Making the Transformation,”Learningand Leading with Technology, vol. 23, no. 7 (Apr1996): 25–30.

14. Janos Setenyi, “Teaching Democracy in an Upopular Democracy,” paper presented at “What tTeach about Hungarian Democracy” conferenceMay 12, 1995, Kossuth Klub, Hungary.

15. Thomas L. Friedman,The World Is Flat: A Brief tory of the Twenty-First Century(New York: FarrarStraus and Giroux, 2006).

16. Steve Ehrmann, “Rewards (?) for Faculty, Depments That Improve,”TLT-SWG , May 24, 2007<http://tlt-swg.blogspot.com/2007_05_01_archiv.html>.

17. Brenna Veale, perso nal communicati on witChuck Dziuban, November 17, 2006.

18. John S. Camp, Peter B. DeBlois, and the EDCAUSE Current Issues Committee, “CurreIssues Survey Report, 2007,”EQ: EDUCAUSQuarterly, vol. 30, no. 2 (2007): 12–31, <http://w.educause.edu/eq/eqm07/eqm0723.asp>.

19. Carol A. Twigg,Improving Learning and RedCosts: Redesigning Large-Enrollment Cour, Pew Learning and Technology Program (Troy, N.YCenter for Academic Transformation, RensselaePolytechnic Institute, 1999), <http://www.cent.rpi.edu/Monographs/mono1.pdf>.

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